A scalable decision tree system and its application in pattern recognition and intrusion detection

[1]  Leo Breiman,et al.  Bagging Predictors , 1996, Machine Learning.

[2]  Foster J. Provost,et al.  A Survey of Methods for Scaling Up Inductive Algorithms , 1999, Data Mining and Knowledge Discovery.

[3]  JOHANNES GEHRKE,et al.  RainForest—A Framework for Fast Decision Tree Construction of Large Datasets , 1998, Data Mining and Knowledge Discovery.

[4]  Olvi L. Mangasarian,et al.  Mathematical Programming in Data Mining , 1997, Data Mining and Knowledge Discovery.

[5]  P. Utgoff,et al.  Multivariate Decision Trees , 1995, Machine Learning.

[6]  John Mingers,et al.  An Empirical Comparison of Pruning Methods for Decision Tree Induction , 1989, Machine Learning.

[7]  J. Ross Quinlan,et al.  Induction of Decision Trees , 1986, Machine Learning.

[8]  Selwyn Piramuthu,et al.  On learning to predict Web traffic , 2003, Decis. Support Syst..

[9]  James T. C. Teng,et al.  Multivariate decision trees using linear discriminants and tabu search , 2003, IEEE Trans. Syst. Man Cybern. Part A.

[10]  Ian H. Witten,et al.  Data mining: practical machine learning tools and techniques with Java implementations , 2002, SGMD.

[11]  Xiaoning Zhang,et al.  Data Mining for Network Intrusion Detection: A Comparison of Alternative Methods , 2001, Decis. Sci..

[12]  Sankar K. Pal,et al.  Pattern Recognition: From Classical to Modern Approaches , 2001 .

[13]  James T. C. Teng,et al.  A Dynamic Programming Based Pruning Method for Decision Trees , 2001, INFORMS J. Comput..

[14]  Huan Liu,et al.  Instance Selection and Construction for Data Mining , 2001 .

[15]  Olivia R. Liu Sheng,et al.  Automated learning of patient image retrieval knowledge: neural networks versus inductive decision trees , 2000, Decis. Support Syst..

[16]  Salvatore J. Stolfo,et al.  A framework for constructing features and models for intrusion detection systems , 2000, TSEC.

[17]  Denis J. Dean,et al.  Comparative accuracies of artificial neural networks and discriminant analysis in predicting forest cover types from cartographic variables , 1999 .

[18]  Salvatore J. Stolfo,et al.  Mining in a data-flow environment: experience in network intrusion detection , 1999, KDD '99.

[19]  João Gama,et al.  Linear tree , 1999, Intell. Data Anal..

[20]  Surajit Chaudhuri,et al.  On the Efficient Gathering of Sufficient Statistics for Classification from Large SQL Databases , 1998, KDD.

[21]  George H. John.  Enhancements to the data mining process , 1997 .

[22]  W. Loh,et al.  SPLIT SELECTION METHODS FOR CLASSIFICATION TREES , 1997 .

[23]  Rakesh Agrawal,et al.  SPRINT: A Scalable Parallel Classifier for Data Mining , 1996, VLDB.

[24]  Jorma Rissanen,et al.  SLIQ: A Fast Scalable Classifier for Data Mining , 1996, EDBT.

[25]  Yoav Freund,et al.  A decision-theoretic generalization of on-line learning and an application to boosting , 1997, EuroCOLT.

[26]  Simon Kasif,et al.  A System for Induction of Oblique Decision Trees , 1994, J. Artif. Intell. Res..

[27]  Teresa F. Lunt,et al.  A survey of intrusion detection techniques , 1993, Comput. Secur..

[28]  J. Ross Quinlan,et al.  C4.5: Programs for Machine Learning , 1992 .

[29]  J. Ross Quinlan,et al.  Simplifying decision trees , 1987, Int. J. Hum. Comput. Stud..

[30]  Dorothy E. Denning,et al.  An Intrusion-Detection Model , 1987, IEEE Transactions on Software Engineering.

[31]  King-Sun Fu,et al.  Handbook of pattern recognition and image processing , 1986 .

[32]  G. V. Kass.  An Exploratory Technique for Investigating Large Quantities of Categorical Data , 1980 .

[33]  V. Barnett,et al.  Applied Linear Statistical Models , 1975 .

[34]  Alfred Benjamin Garrett,et al.  The Flash of Genius , 2012 .